In [3]:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import warnings
warnings.filterwarnings("ignore")
import os
import base64
from multiprocessing.managers import BaseManager
from mpl_toolkits.basemap import Basemap
import matplotlib.patches as mpatches
import io
from matplotlib import animation, rc 
import folium
import folium.plugins
from IPython.core.display import display, HTML
import codecs
from subprocess import check_output
In [5]:
terror_csv = pd.read_csv(r"D:\GitHub\World_Terrorism_Analysis\gtd_data.csv",encoding="ISO-8859-1") 

terror_csv.rename(columns={'iyear':'Year','imonth':'Month','iday':'Day','country_txt':'Country', 'city':'City', 'latitude':'Latitude', 'longitude':'Longitude', 'attacktype1_txt':'AttackType', 'nkill':'Death', 'nwound':'Injured', 'gname':'Attacker','targtype1_txt':'TargetType','weaptype1_txt':'WeaponType', 'weapsubtype1_txt':'WeaponSubType'},inplace=True)
terror_csv=terror_csv[["Year","Month","Day","Country","City","Latitude","Longitude","AttackType","Death","Injured","Attacker","TargetType","WeaponType","WeaponSubType"]]

Exploratory Data Analysis

In [5]:
terror_csv.head()
Out[5]:
Year Month Day Country City Latitude Longitude AttackType Death Injured Attacker TargetType WeaponType WeaponSubType
0 1970 7 2 Dominican Republic Santo Domingo 18.456792 -69.951164 Assassination 1.0 0.0 MANO-D Private Citizens & Property Unknown NaN
1 1970 0 0 Mexico Mexico city 19.371887 -99.086624 Hostage Taking (Kidnapping) 0.0 0.0 23rd of September Communist League Government (Diplomatic) Unknown NaN
2 1970 1 0 Philippines Unknown 15.478598 120.599741 Assassination 1.0 0.0 Unknown Journalists & Media Unknown NaN
3 1970 1 0 Greece Athens 37.997490 23.762728 Bombing/Explosion NaN NaN Unknown Government (Diplomatic) Explosives Unknown Explosive Type
4 1970 1 0 Japan Fukouka 33.580412 130.396361 Facility/Infrastructure Attack NaN NaN Unknown Government (Diplomatic) Incendiary NaN
In [6]:
terror_csv.shape
Out[6]:
(181691, 14)
In [7]:
terror_csv.describe()
Out[7]:
Year Month Day Latitude Longitude Death Injured
count 181691.000000 181691.000000 181691.000000 177135.000000 1.771340e+05 171378.000000 165380.000000
mean 2002.638997 6.467277 15.505644 23.498343 -4.586957e+02 2.403272 3.167668
std 13.259430 3.388303 8.814045 18.569242 2.047790e+05 11.545741 35.949392
min 1970.000000 0.000000 0.000000 -53.154613 -8.618590e+07 0.000000 0.000000
25% 1991.000000 4.000000 8.000000 11.510046 4.545640e+00 0.000000 0.000000
50% 2009.000000 6.000000 15.000000 31.467463 4.324651e+01 0.000000 0.000000
75% 2014.000000 9.000000 23.000000 34.685087 6.871033e+01 2.000000 2.000000
max 2017.000000 12.000000 31.000000 74.633553 1.793667e+02 1570.000000 8191.000000
In [8]:
terror_csv.isnull().sum()
Out[8]:
Year                 0
Month                0
Day                  0
Country              0
City               434
Latitude          4556
Longitude         4557
AttackType           0
Death            10313
Injured          16311
Attacker             0
TargetType           0
WeaponType           0
WeaponSubType    20768
dtype: int64

Basic Analysis

In [9]:
print("Known Count of Deaths in Terrorist Attacks:", terror_csv["Death"].value_counts()[0], "\n")

print("Country With The Highest Terrorist Attacks:", terror_csv["Country"].value_counts().index[0], "\n")

print("Most deaths in an attack:\n",terror_csv.loc[terror_csv['Death'].idxmax()], "\n")

Known Count of Deaths in Terrorist Attacks: 88149 

Country With The Highest Terrorist Attacks: Iraq 

Most deaths in an attack:
 Year                                                    2014
Month                                                      6
Day                                                       12
Country                                                 Iraq
City                                                  Tikrit
Latitude                                           34.621521
Longitude                                          43.668377
AttackType                       Hostage Taking (Kidnapping)
Death                                                 1570.0
Injured                                                  NaN
Attacker         Islamic State of Iraq and the Levant (ISIL)
TargetType                                          Military
WeaponType                                          Firearms
WeaponSubType                               Unknown Gun Type
Name: 133518, dtype: object
In [10]:
plt.subplots(figsize=(15,6))
sns.countplot(data=terror_csv, x="Year", palette="mako")
plt.xticks(rotation=90)
plt.title('Terrorist Attacks Each Year')
plt.show()
In [11]:
plt.subplots(figsize=(12,6))
sns.countplot(data=terror_csv, x="TargetType", order=terror_csv["TargetType"].value_counts().index, palette="rocket")
plt.xticks(rotation=90)
plt.title('Terrorist Attacks Each Target')
plt.show()
In [12]:
plt.subplots(figsize=(8,6))
sns.countplot(data=terror_csv, x="AttackType", order=terror_csv["AttackType"].value_counts().index, palette="rocket")
plt.xticks(rotation=90)
plt.title('Terrorist Attacks Each Attack Type')
plt.show()
In [13]:
plt.subplots(figsize=(10,6))
sns.barplot(x = terror_csv["Country"].value_counts()[:10].index,y= terror_csv["Country"].value_counts()[:10].values, palette="rocket")
plt.xticks(rotation=90)
plt.title('Top 10 Affected Countries')
plt.show()
In [14]:
plt.subplots(figsize=(8,6))
sns.barplot(x = terror_csv["Attacker"].value_counts()[1:11].values, y= terror_csv["Attacker"].value_counts()[1:11].index , palette="rocket")
plt.title('Terrorist Groups with the Most Attacks')
plt.show()
In [6]:
def color_point(x):
    if x>=30:
        color='red'
    elif ((x>0 and x<30)):
        color='blue'
    else:
        color='green'
    return color  
    
def point_size(x):
    if (x>30 and x<100):
        size=2
    elif (x>=100 and x<500):
        size=8
    elif x>=500:
        size=16
    else:
        size=0.5
    return size   

terror_turkey=terror_csv[terror_csv["Country"]=="Turkey"]
terror_turkey_fol=terror_turkey.copy()
terror_turkey_fol.dropna(subset=["Latitude","Longitude"],inplace=True)
location_tr=terror_turkey_fol[["Latitude","Longitude"]][:5000]
city_tr=terror_turkey_fol["City"][:5000]
Death_tr=terror_turkey_fol["Death"][:5000]
Injured_tr=terror_turkey_fol["Injured"][:5000]
target_tr=terror_turkey_fol["TargetType"][:5000]

map1 = folium.Map(location=[39.1667, 35.6667],tiles='CartoDB dark_matter',zoom_start=6.4)
for point in location_tr.index:
    folium.CircleMarker(list(location_tr.loc[point].values),popup='<b>City: </b>'+str(city_tr[point])+'<br><b>Killed: </b>'+str(Death_tr[point])+'<br><b>Injured: </b>'+str(Injured_tr[point])+'<br><b>Target: </b>'+str(target_tr[point]),radius=point_size(Death_tr[point]),color=color_point(Death_tr[point]),fill_color=color_point(Death_tr[point])).add_to(map1)
map1
Out[6]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [17]:
fig, ax = plt.subplots(figsize = (7,4))
def animate(Year):
    ax.clear()
    ax.set_title('Terrorism In Turkey\n'+ str(Year))
    map2 = Basemap(projection='lcc',resolution='l' ,width=1800000, height=900000 ,lat_0=38.9637, lon_0=35.2433)
    lat_gif=list(terror_turkey[terror_turkey['Year']==Year].Latitude)
    long_gif=list(terror_turkey[terror_turkey['Year']==Year].Longitude)
    x_gif,y_gif=map2(long_gif,lat_gif)
    map2.scatter(x_gif, y_gif,s=[Death+Injured for Death,Injured in zip(terror_turkey[terror_turkey['Year']==Year].Death,terror_turkey[terror_turkey['Year']==Year].Injured)],color = 'r')
    map2.drawcoastlines()
    map2.drawcountries()
    map2.fillcontinents(color='Black',lake_color='white', zorder = 1,alpha=0.4)
    map2.drawmapboundary()
ani = animation.FuncAnimation(fig,animate, list(terror_turkey.Year.unique()), interval = 1500) 

ani.save('animation_tr.gif', writer='imagemagick', fps=1)
plt.close(1)
filename = 'animation_tr.gif'
video = io.open(filename, 'r+b').read()
encoded = base64.b64encode(video)
HTML(data='''<img src="data:image/gif;base64,{0}" type="gif" />'''.format(encoded.decode('ascii')))
Out[17]:
In [18]:
fig, ax = plt.subplots(figsize = (10,6))
def animate(Year):
    ax.clear()
    ax.set_title('Animation Of Terrorist Activities'+'\n'+'Year:' +str(Year))
    map3 = Basemap(projection='mill',llcrnrlat=-80,urcrnrlat=80, llcrnrlon=-180,urcrnrlon=180,lat_ts=20,resolution='c')
    lat3=list(terror_csv[terror_csv['Year']==Year].Latitude)
    long3=list(terror_csv[terror_csv['Year']==Year].Longitude)
    x3,y3=map3(long3,lat3)
    map3.scatter(x3, y3,s=[(Death+Injured)*0.1 for Death,Injured in zip(terror_csv[terror_csv['Year']==Year].Death,terror_csv[terror_csv['Year']==Year].Injured)],color = 'r')
    map3.drawcoastlines()
    map3.drawcountries()
    map3.fillcontinents(color='Black',lake_color='white', zorder = 1,alpha=0.4)
    map3.drawmapboundary()
ani = animation.FuncAnimation(fig,animate,list(terror_csv.Year.unique()), interval = 1500)    
ani.save('animation.gif', writer='imagemagick', fps=1)
plt.close(1)
filename = 'animation.gif'
video = io.open(filename, 'r+b').read()
encoded = base64.b64encode(video)
HTML(data='''<img src="data:image/gif;base64,{0}" type="gif" />'''.format(encoded.decode('ascii')))
Out[18]: